Roehe, R. | Search bioRxiv

bioRxiv2018

Open prediction of polysaccharide utilisation loci (PUL) in 5414 public Bacteroidetes genomes using PULpy

Polysaccharide utilisation loci (PUL) are regions within bacterial genomes that encode all the necessary machinery for the cleavage of particular carbohydrates. For the Bacteroidetes phylum, prediction of PUL from genomic data alone involves the identification of carbohydrate-active enzymes (CAZymes) co-localised with susCD gene pairs. Here we present the open prediction of PUL in 5414 public Bacteroidetes genomes, and an open-source pipeline to reproduce or extend the results.

microbiology↗

bioRxiv2017

MAGpy: a reproducible pipeline for the downstream analysis of metagenome-assembled genomes (MAGs)

Recent advances in bioinformatics have enabled the rapid assembly of genomes from metagenomes (MAGs), and there is a need for reproducible pipelines that can annotate and characterise thousands of genomes simultaneously. Here we present MAGpy, a Snakemake pipeline that takes FASTA input and compares MAGs to several public databases, checks quality, assigns a taxonomy and draws a phylogenetic tree.

bioinformatics↗

bioRxiv2017

Assembly of hundreds of microbial genomes from the cow rumen reveals novel microbial species encoding enzymes with roles in carbohydrate metabolism

The cow rumen is a specialised organ adapted for the efficient breakdown of plant material into energy and nutrients, and it is the rumen microbiome that encodes the enzymes responsible. Many of these enzymes are of huge industrial interest. Despite this, rumen microbes are under-represented in the public databases. Here we present 220 high quality bacterial and archaeal genomes assembled directly from 768 gigabases of rumen metagenomic sequence data. Comparative analysis with current publicly available genomes reveals that the majority of these represent previously unsequenced strains and species of bacteria and archaea. The genomes contain over 13,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in the public databases. Inclusion of the 220 genomes presented here improves metagenomic read classification by 2-3-fold, both in our data and in other publicly available rumen datasets. This release improves the coverage of rumen microbes in the public databases, and represents a hugely valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome

genomics↗